… literature on inference in difference-in-differences designs with … Second, the main problem
in difference-in-differences … Third, feasible GLS estimation combined with robust inference …

… Difference-in-differences (DID) estimation has become increasingly popular as an approach
to evaluate the effect of a group-level policy on individual-level outcomes. Several statistical …

… Estimation and inference procedures for the treatment effects of interest are presented in
Section 4. We revisit the effect of minimum wage on employment in Section 5. Section 6 …

… for inference in difference-in-differences (… Difference-in-Differences (DID) is one of the most
widely used methods for identification of causal effects in social sciences. However, inference …

… other, we first revisit the California smoking cessation … inference. We postpone a discussion
of confidence intervals until Section IV, where we consider various strategies for inference …

… our inference method … inference methods and to compare that to the performance of our
method with heteroskedasticity correction in section V, while we compare the different inference …

… compare to each other, we first revisit the California smoking cessation program example of
… ], who focus on valid inference in difference in differences settings when users look at past …

… “Difference-in-differences” (DiD) is a workhorse estimation approach for making causal
inference in these … in the outcomes between treated and controls over time to infer causal effects. …

… borders, classical difference-in-differences estimation produces … To highlight the importance
of spillover effects, I revisit … Since ˆτ is a linear combination of sample averages, inference …

I derive simple, flexible strategies for difference-in-differences settings where the nature of
the response variable may warrant a nonlinear model. I allow for general staggered …